Collabera Wells Fargo - AI Engineer (Forward-Deployed AI Engineer)

AI Engineer -

Forward-Deployed AI Engineer Client:

Wells Fargo Hiring Manager:

Rachit Mathur Location:

Charlotte, NC Work Model:

Hybrid (3 days onsite)

Duration:

9+

Month Contract Start Date:

ASAP Line of Business:

COO Visa:

/ /L2/h1b/E3/J2 Overview We are seeking a highly technical and business-oriented Forward-Deployed AI Engineer to help design, build, and deploy enterprise-grade AI solutions that drive measurable business outcomes across the organization. This role sits at the intersection of AI engineering, enterprise platforms, and business problem-solving. The ideal candidate will operate as a hybrid of a software engineer, AI solutions architect, and technical consultant - partnering directly with business, product, and engineering stakeholders to rapidly prototype and productionize AI-powered workflows, copilots, automations, and agentic systems. The environment is fast-paced and highly collaborative, requiring someone comfortable navigating ambiguous problem spaces while delivering scalable and secure enterprise solutions. Key Responsibilities Partner with business, product, and engineering teams to identify and define AI-driven solutions Design and build AI workflows, copilots, automations, and agentic systems using LLM technologies Develop and deploy scalable AI applications in enterprise production environments Integrate AI solutions with enterprise platforms such as ServiceNow, Salesforce, and internal systems through APIs Build and optimize Retrieval-Augmented Generation (RAG) pipelines and orchestration frameworks Lead architecture discussions around prompt engineering, orchestration, APIs, and data integration Rapidly prototype solutions and transition them into production-ready systems Collaborate across business, engineering, security, and governance teams Ensure AI implementations align with enterprise security, risk, and compliance standards Contribute reusable AI frameworks, engineering standards, and best practices Own the full solution lifecycle from concept and POC through deployment and optimization Required Qualifications 7+ years of software engineering experience building production-grade applications Strong hands-on Python development experience Experience building and deploying AI/ML applications in enterprise environments 2+ years of hands-on experience with LLM-based solutions and AI workflows Strong experience with APIs, integrations, and distributed systems Experience designing scalable end-to-end enterprise solutions Ability to translate ambiguous business problems into technical solutions Strong communication and stakeholder management skills Preferred Qualifications Experience with OpenAI, Anthropic, LangChain, or similar AI platforms/frameworks Experience building AI agents, copilots, and RAG-based applications Integration experience with ServiceNow, Salesforce, or enterprise workflow platforms Experience working within regulated environments such as financial services Exposure to enterprise governance, security, and risk frameworks Consulting or customer-facing engineering experience Product-oriented mindset with strong focus on user experience and business impact Technical Environment Python LLMs / Generative AI OpenAI / Anthropic APIs LangChain / Agentic Frameworks RAG Architectures APIs & Enterprise Integrations Distributed Systems Prompt Engineering AI Automation Platforms Cloud & Enterprise Platforms Ideal Candidate The ideal candidate is someone who combines strong software engineering fundamentals with hands-on AI implementation experience and the ability to work directly with stakeholders to solve complex business problems. This person should be equally comfortable architecting enterprise solutions, writing production-grade code, and driving AI adoption across cross-functional teams.